Pamela Lustig

Background: This study reports the development and initial face and content validation of high-fidelity 3D hybrid simulators for training in complex pediatric oncologic surgery. Pediatric solid tumor surgery is technically demanding; case volumes are low, and procedural errors carry lifelong oncologic or functional consequences. High-fidelity simulation offers a route to structured training without patient risk. Methods: Patient-derived hybrid simulators were developed by combining 3D-printed anatomical molds with multi-hardness platinum silicone casting. Three oncologic scenarios were reproduced: nephron-sparing surgery (NSS) for Wilms tumor, neuroblastoma L1, and neuroblastoma L2 with major vascular involvement. Retrospective imaging datasets were segmented using Philips IntelliSpace Portal to generate patient-derived STL files. Bony components (simulator box, thoracic wall) were fabricated by selective laser sintering (SLS) in PA12 polyamide. Silicone casting molds were produced by fused filament fabrication (FFF) in basic PLA. Silicone selection (Smooth-On Ecoflex and Dragon Skin series) was based on our team’s expertise in the mechanical characteristics of human organs, matching manufacturer-provided Shore hardness datasheet values to the closest available reference for each tissue type. All components were assembled in anatomically accurate sequence within a patient-sized housing box. Validation was conducted through structured workshops with fifteen pediatric surgical oncologists using a 5-point Likert scale. Results: Mean Likert scores, calculated from participant-level composite domain scores (n = 27 model evaluations from 15 participants), were high across all domains: anatomical accuracy 4.14 ± 0.53 (median 4.00, IQR 3.67–4.67), dissection realism 4.29 ± 0.45 (median 4.33, IQR 4.00–4.50), and tactile fidelity 4.37 ± 0.56 (median 4.00, IQR 4.00–5.00). The L2 neuroblastoma model was rated particularly valuable for rehearsing synchronized two-surgeon workflows and anticipatory communication during high-risk vascular dissection. Conclusions: These hybrid simulators provide a reproducible, high-fidelity platform with strong expert-perceived realism, supporting rehearsal of technical maneuvers and coordinated two-surgeon workflows; formal evaluation of skill acquisition and clinical transfer remains warranted.

Digital three-dimensional (3D) visualization is an evolving field that is being introduced into pediatric surgical oncology, where it addresses challenges related to complex anatomy and difficulties accurately defining surgical margins. This paper provides an overview of digital 3D modeling in pediatric surgical oncology and explores ways to further advance this field. Digital 3D models may improve various aspects of surgery, such as preoperative planning, intraoperative guidance, patient education, and surgical training. Traditionally, 3D models are manually or semi-automatically segmented. More recently, artificial intelligence (AI) can automatically segment pediatric solid tumors. For preoperative planning, 3D models improve anatomic understanding and help multidisciplinary communication. During surgery, these models can assist the surgeon in accurately localizing tumors and determining resection margins in preclinical research settings. In patient education, 3D models present an opportunity to improve patient understanding of disease, therapy, and surgical risks. Lastly, digital 3D models are used in surgical training, particularly for challenging cases. Although digital 3D technologies are evaluated using technical performance metrics, these measures do not necessarily result in improved clinical outcomes. Consequently, evidence demonstrating improved surgical outcomes remains limited, also due to the small patient cohorts. Several challenges continue to hinder clinical translation, including image quality and standardization, segmentation complexity, organ deformability during surgery, and insufficient clinical validation. Addressing these limitations will require progress in four key areas: AI integration, multicenter validation, the development of centralized infrastructures including digital twins, and scalable implementation strategies that support widespread clinical adoption.

Introduction: Pediatric oncology patients use totally implantable venous access devices (TIVADs) to enable central venous access. Anxiety, pain and/or discomfort are common despite anesthesia. Virtual reality (VR) is a non-pharmacological approach that may reduce pain and anxiety in these patients. We aimed to assess the use of VR for reducing anxiety/pain in patients with TIVADs while facilitating the task of healthcare providers when accessing a TIVAD. Methods: patients 4–18 years old with a TIVAD were prospectively randomized to an intervention group (IG) or a control group (CG). In the IG, VR goggles (Oculus Quest 2, Meta Platforms^®, Menlo Park, CA, USA) were used displaying a relaxing video in the Raja Ampat environment (Ecosphere app from Phoria^®) while the TIVAD was accessed. The CG was managed as per standard of care. Satisfaction and pain were measured by FPS-R and STAIC scales, respectively. Results: this is the report of a prospective, randomized (60 per group)—unblinded—, single institution study of 120 pediatric oncology patients enrolled from January to April 2022. Median ages for IG and CG were 9.22 and 10.52 years, respectively. Satisfaction was higher in the IG (4.80) compared to the CG (3.92), p ≤ 0.0001. Regarding pain, mean FPS-R scores were 1.79 for the CG and 0.83 for the IG. Significantly different scores were found in the 12 to 18 years group, p ≤ 0.05. The healthcare professionals index of satisfaction was high (4.50 mean Likert score) for the IG compared to accessing the TIVAD without VR (3.73 mean Likert score). Conclusion: The use of VR helped reduce pain and/or discomfort in pediatric oncology patients, mainly in the older age group as they can better interact with VR. Healthcare providers were satisfied with the help of VR for TIVAD management.

The printing and manufacturing of anatomical 3D models has gained popularity in complex surgical cases for surgical planning, simulation and training, the evaluation of anatomical relations, medical device testing and patient–professional communication. 3D models provide the haptic feedback that Virtual or Augmented Reality (VR/AR) cannot provide. However, there are many technologies and strategies for the production of 3D models. Therefore, the aim of the present study is to show and compare eight different strategies for the manufacture of surgical planning and training prototypes. The eight strategies for creating complex abdominal oncological anatomical models, based on eight common pediatric oncological cases, were developed using four common technologies (stereolithography (SLA), selectie laser sinterning (SLS), fused filament fabrication (FFF) and material jetting (MJ)) along with indirect and hybrid 3D printing methods. Nine materials were selected for their properties, with the final models assessed for application suitability, production time, viscoelastic mechanical properties (shore hardness and elastic modulus) and cost. The manufacturing and post-processing of each strategy is assessed, with times ranging from 12 h (FFF) to 61 h (hybridization of FFF and SLS), as labor times differ significantly. Cost per model variation is also significant, ranging from EUR 80 (FFF) to EUR 600 (MJ). The main limitation is the mimicry of physiological properties. Viscoelastic properties and the combination of materials, colors and textures are also substantially different according to the strategy and the intended use. It was concluded that MJ is the best overall option, although its use in hospitals is limited due to its cost. Consequently, indirect 3D printing could be a solid and cheaper alternative.